A wide variety of cancer treatment protocols have been developed in recent years. Often, very aggressive cancer therapy is reserved for late stage cancers due to unwanted side effects produced by such therapy. However, even such aggressive therapy commonly fails at such a late stage. The ability to identify cancers responsive only to the most aggressive therapies at an earlier stage could greatly improve the prognosis for patients having such cancers.
Only very recently, however, have markers predictive of such outcomes been identified. Glinsky, G. V. et al., J. Clin. Invest. 113: 913-923 (2004) teaches that gene expression profiling predicts clinical outcomes of prostate cancer. van 't Veer et al., Nature 415: 530-536 (2002) teaches that gene expression profiling predicts clinical outcomes of breast cancer. Glinsky et al., J. Clin. Invest. 115: 1503-1521 (2005) teaches that altered expression of the BMI1 oncogene is functionally linked with self-renewal state of normal and leukemic stem cells as well as a poor prognosis profile of an 11-gene death-from-cancer signature predicting therapy failure in patients with multiple types of cancer. These studies utilized the microarray gene expression analysis approach.
There is, therefore, a need for methods for early diagnosis of cancer and for prognostic assays for cancer therapy that are readily adaptable to the clinical setting. Such methods should utilize technologies that can be readily carried out in clinical laboratories, and should accurately predict the resistance of various cancers to be applied to standard therapeutic regimens.